Senior Director of Product Management, Merchandising

Senior Director of Product Management, Merchandising

Paramount+ is seeking a Senior Director of Product Management, Merchandising to lead how audiences discover and engage with content across our global streaming platform. This role defines the global strategy and aligns teams around execution for content promotion, curation enablement, and personalization across all platforms. This is to ensure that editorial intent, data intelligence, and product capabilities work collectively to deliver intuitive, compelling viewer experiences at scale. Operating at the intersection of Product, Programming, Machine Learning, Design, and Operations, this role will translate business and content priorities into measurable merchandising outcomes that boosts interaction, retention, and long-term subscriber value worldwide.

Primary Responsibilities:

• Define and own the global merchandising and content presentation strategy across all content types, platforms, and markets.
• Translate business and content priorities into a clear merchandising roadmap aligned to quarterly and annual OKRs.
• Lead the operationalization of merchandising at scale, establishing end-to-end workflows that support global execution while enabling local relevance.
• Partner closely with Product, Engineering and Applied Machine Learning (AMLG) leads to shape feature ideation, user stories, acceptance criteria, and roadmap decisions informed by merchandising insights.
• Oversee monitoring and reporting to surface insights and drive continuous optimization.
• Drive experimentation, ensuring readiness for A/B and multivariate testing through solid metadata, creative, and operational foundations.
• Partner with Content Services and Programming teams to ensure metadata quality, taxonomy alignment, and system integrity across internal and consumer-facing tools.
• Act as a senior connective leader across Programming, Marketing, Product, AMLG, Design, and Business Insights to ensure strategic alignment.
• Lead, mentor, and scale a lean, high-performing merchandising team, setting clear standards for execution, communication, and accountability.

Basic Qualifications:

• 8+ years of experience leading consumer-facing digital products or experiences at scale, preferably in streaming, media, or entertainment environments.
• 5+ years of experience managing and developing high-performing teams across product, merchandising, content, or data functions at a senior level.
• Bachelor's degree required; technical or quantitative discipline strongly preferred.
• Demonstrated expertise applying data science methodologies (e.g., segmentation, predictive modeling, behavioral analytics) to drive measurable business outcomes such as subscriber growth, engagement, retention, or revenue.
• Deep knowledge of personalization systems and recommendation algorithms, with the ability to influence ML roadmap direction and collaborate closely with engineering and data science teams.
• Experience defining content architecture and curation strategy at platform scale, with a strong understanding of how system dependencies impact the end-user experience.
• Proven track record of owning end-to-end product outcomes, including defining success metrics, measuring performance, and driving continuous improvement.
• Demonstrated ability to influence and align cross-functional stakeholders, including executive, technical, and creative teams, in a fast-paced, matrixed environment.
• Experience operating at scale, including ownership of large user bases, complex product ecosystems, or global platforms.
• Exceptional communication skills with the ability to synthesize quantitative findings and influence executive, technical, and creative stakeholders.

Preferred Qualifications:

• MBA, M.S. in Data Science, Statistics, Computer Science, or related quantitative field, or equivalent experience at senior level.
• Experience leading merchandising or content discovery for a global streaming platform, with a proven record of driving decisions through experimentation and rigorous measurement.
• Proficiency with analytics and data science tooling including Adobe Analytics, Tableau, Looker, Python, R, or SQL.
• Familiarity with data modeling, feature engineering, or co-developing ranking inputs alongside data science and ML teams.
• Experience operating across multiple international markets and time zones.